code: def _replace_tensors_for_gradient(x, grad):
      """Replaces the tensors in `x` that should be differentiated with `grad`.
  
      Args:
        x: A `Tensor` or `CompositeTensor`.
        grad: A nested structure of `Tensor`, with the same structure as the value
          returned by `_get_tensors_for_gradient(x)`.
  
      Returns:
        A `Tensor` or `CompositeTensor`.
      """
      if not isinstance(x, composite_tensor.CompositeTensor):
          return grad
  
      if not isinstance(x, CompositeTensorGradientProtocol):
          raise ValueError(
              f"Type {type(x).__name__} is not supported as a gradient source."
          )
  
      composite_gradient = x.__composite_gradient__
      x_components = composite_gradient.get_gradient_components(x)
      if x_components is x:
          grad_components = grad
      else:
          grad_components = nest.map_structure_up_to(
              x_components,
              _replace_tensors_for_gradient,
              x_components,
              grad,
          )
      if grad_components is None:
          return None
      return composite_gradient.replace_gradient_components(
          x, grad_components
      )
  
file_path: tensorflow-upstream/tensorflow/python/framework/composite_tensor_gradient.py
imports: import abc
  import sys
  from tensorflow.python.framework import composite_tensor
  from tensorflow.python.util import nest
label_desc: Use image node_id 2 for calling a global function with example usage: _replace_tensors_for_gradient(x, grad) and returns: composite_gradient, grad, None